Extension of the MPEG-7 Fourier Feature Descriptor for face recognition using PCA

N. Zaeri, F. Mokhtarian, A. Cherri
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Abstract

The Principal Component Analysis or the eigenface technique provides a practical solution to the problem of face recognition. Recently, many face descriptors for MPEG-7 have been proposed for face retrieval in video streams. In this paper, a new method for face recognition is presented based on extracting the most discriminant features of the MPEG-7 Fourier Feature Descriptors of the face space, defined by MPEG-7 face recognition technique, through the implementation of the eigenface technique. It will be demonstrated that the proposed method improves the recognition rate and copes better with pose variations under different facial expressions and varying face conditions, as well as illumination variations. In addition, the proposed method achieves substantial savings in the computation time needed by the recognition system.
基于PCA的MPEG-7傅里叶特征描述符人脸识别扩展
主成分分析或特征脸技术为人脸识别问题提供了一个实用的解决方案。近年来,针对视频流中的人脸检索,已经提出了许多针对MPEG-7的人脸描述符。本文提出了一种基于MPEG-7人脸识别技术定义的人脸空间的傅里叶特征描述子,通过实现特征脸技术提取最具判别性特征的人脸识别新方法。结果表明,该方法提高了识别率,更好地处理了不同面部表情和不同面部条件下的姿态变化,以及光照变化。此外,该方法大大节省了识别系统所需的计算时间。
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